Evidence map›Paper›PMID 35126635›Full record

Observational studyComputational and mathematical methods in medicine2022

Three-Dimensional Skin CT Based on Intelligent Algorithm in the Analysis of Skin Lesion Sites Features in Children with Psoriasis.

Lina Wang, Youning Zheng, Ran Zhou, Wenfang Liu

RetractedOpen access · hybridAbstract readObservational StudyRetracted Publication
In one paragraph

Observational study in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 38% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Lina WangDepartment of Dermatology, Hanzhong People's Hospital, Hanzhong, 723000 Shaanxi, China.ORCID https://orcid.org/0000-0002-2970-8489
Youning ZhengDepartment of Pediatrics, Hebei General Hospital, Shijiazhuang, 050051 Hebei, China.ORCID https://orcid.org/0000-0002-0146-5307
Ran ZhouDepartment of Pediatrics, Hebei General Hospital, Shijiazhuang, 050051 Hebei, China.ORCID https://orcid.org/0000-0001-7716-137X
Wenfang LiuSurgery Teaching and Research Office, Cangzhou Medical College, Cangzhou, 061001 Hebei, China.ORCID https://orcid.org/0000-0001-9494-8035
Hebei General Hospital · CNHanzhong People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This research was to explore the application value of three-dimensional computed tomography (CT) based on artificial intelligent algorithm in analyzing the characteristics of skin lesions in children with psoriasis. In this study, 15 children with psoriasis were selected as the observation group, and 15 children with other skin diseases were selected as the control group. The CT images were optimized, and the feature selection was carried out based on artificial intelligent algorithm. Firstly, the results were compared with the results of simple skin three-dimensional CT to determine the effectiveness. Then, the two groups of three-dimensional skin CT image features of skin psoriasis-like hyperplasia, Munro microabscess, dermal papillary vascular dilation, and squamous epithelium based on intelligent algorithms were compared. After comparison, the detection rate of psoriasis-like hyperplasia, Munro microabscess, dermal papillary vascular dilation, and squamous epithelium in the observation group was higher than that in the control group, with significant difference and statistical significance (

Indexed as

AlgorithmsAbscessArtificial IntelligenceCase-Control StudiesChildComputational BiologyComputer SimulationDermisEpitheliumFemaleHumansHyperplasiaImaging, Three-DimensionalMaleMicroscopy, ConfocalPsoriasis

Identifiers

PMID35126635
PMCPMC8816560
OpenAlexW4210739227

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.